Implementing an iterative reconstruction algorithm for digital breast tomosynthesis on graphics processing hardware

The Maximum Likelihood Expectation Maximization (MLEM) algorithm has been shown to produce the highest quality Digital Breast Tomosynthesis (DBT) images. MLEM, however, is computationally intensive. Single-processor image reconstruction times for each breast were on the order of several hours. In order for DBT to be clinically useful, faster reconstruction times using cost-effective software/hardware solutions are needed. We have implemented the MLEM reconstruction algorithm for use with DBT on a graphics processing unit (GPU). Compared to a single optimized 2.8GHz Pentium system this enabled a 113-fold speedup in processing time, while maintaining high image quality. Subsequently, we added various additional processing steps to the reconstruction algorithm in order to improve image quality and diagnostic properties. Since the performance of commercial GPUs increases rapidly, with little change in cost, the increased sophistication in processing does not entail an increase in system cost. The use of GPUs for reconstruction represents a technical breakthrough in the cost-effective application of MLEM to Digital Breast Tomosynthesis.